Fine Motor Function
Fine Motor Function - Related Videos
05:39
A Fine Motor Task to Study Joint Kinematics in a Preclinical Model of Neurodegenerative Disease
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2025
The current study describes a fine motor behavior test for examining motor deficits in rodent models, including the TgF344-AD rat, using machine learning.
11:31
Functional Near Infrared Spectroscopy of the Sensory and Motor Brain Regions with Simultaneous Kinematic and EMG Monitoring During Motor Tasks
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Cited by 16 •
2014
Monitoring brain activity during upright motor tasks is of great value when investigating the neural source of movement disorders. Here, we demonstrate a protocol that combines functional near infrared spectroscopy with continuous monitoring of muscle and kinematic activity during 4 types of motor tasks.
14:55
Methods to Quantify Pharmacologically Induced Alterations in Motor Function in Human Incomplete SCI
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Cited by 17 •
2011
This video demonstrates modulation of reflex activity, volitional strength and ambulation through clinical and quantitative assessments in individuals with motor incomplete SCI as a result of acute oral administration of a serotonin reuptake inhibitor (SSRI).
06:08
Biophysical Characterization of Flagellar Motor Functions
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Cited by 8 •
2017
Recent findings suggest that bacterial flagellar motors sense a variety of environmental signals and remodel in response. The bead-assays discussed here are expected to help explain the role of remodeling in cellular adaptation to environmental stressors.
08:51
Monitoring Fine and Associative Motor Learning in Mice Using the Erasmus Ladder
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Cited by 1 •
2023
This article presents a protocol that allows a non-invasive and automated assessment of fine motor performance, as well as adaptive and associative motor learning upon challenges, using a device called the Erasmus Ladder. Task difficulty can be titrated to detect motor impairment ranging from major to subtle degrees.
FAQs
Neural signals coordinate the activation of specific muscle groups rather than producing undifferentiated movement. This selective activation helps control the force, timing, and position required for tasks involving the hands and fingers. In bioengineering, understanding this coordination provides a foundation for developing systems that can interpret or reproduce more controlled dexterous movement.
Sensory feedback continuously informs the nervous system about movement conditions, allowing force, timing, and position to be adjusted during a task. Without this ongoing correction, precise control would be more difficult to maintain. Bioengineered systems can therefore be evaluated partly by how effectively they support accurate, responsive adjustment during dexterous activities.
Accuracy depends on the coordinated interaction of neural activation, muscle-group selection, force, timing, position, and sensory feedback. These factors work together rather than independently: neural signals initiate targeted action, while feedback modifies the movement as it unfolds. Measuring several performance dimensions can reveal where control is effective or impaired.
The biological requirements for selective activation and continuous adjustment guide the design of prosthetic limbs and robotic interfaces. Effective systems aim to translate control signals into coordinated movement while supporting appropriate force, timing, and position. These principles help engineers pursue dexterity that is more responsive to the user’s intended actions.
Researchers can assess performance by measuring grip force, movement accuracy, and task performance. Together, these measures indicate how well a person or engineered system controls force and executes coordinated actions. The results can help evaluate motor impairment, compare performance across tasks, and determine whether a rehabilitation or assistive technology supports useful improvements.
Measurements of grip force, movement accuracy, and task performance can help evaluate motor impairment and guide personalized therapy. Rather than relying only on general impressions, these outcomes provide task-related information about control and performance. Bioengineering applications can use the measurements to monitor functional needs and inform rehabilitation approaches tailored to an individual.
Assistive devices must address the control demands of precise hand and finger tasks, including appropriate force, timing, and position. Findings about fine motor function help engineers design technologies that restore or augment dexterity. Such devices can be assessed through task performance and movement accuracy to determine whether they provide meaningful functional support.
Neural engineering may enable more natural and responsive control of engineered limbs by using the relationship between neural signals, muscle activation, and sensory adjustment. The goal is not simply to produce movement, but to support coordinated control that better reflects intended actions. This direction is relevant to future prosthetic technologies designed for improved dexterity.